Skip to content

Aggregating Data Over Time

Purpose:

This application demonstrates how to simulate random events via Feed Simulation and calculate running aggregates such as avg, min, max, etc. The aggregation is executed on events within a time window. A sliding time window of 10 seconds is used in this sample. For more information on windows see Siddhi Query Guide - Window. The group by clause helps to perform aggregation on events grouped by a certain attribute. In this sample, the trading information per trader is aggregated and summarized, for a window of 10 seconds.

Before you begin:

In the Streaming Integrator Tooling, save the sample Siddhi application.

Executing the Sample

To execute the sample open the saved Siddhi application in Streaming Integrator Tooling, and start it by clicking the Start button (shown below) or by clicking Run => Run.

Start button

If the Siddhi application starts successfully, the following message appears in the console.

AggregateOverTime.siddhi - Started Successfully!.

Testing the Sample

To test the sample Siddhi application, simulate random events for it via the Streaming Integrator Tooling as follows:

  1. To open the Event Simulator, click the Event Simulator icon.

    Event Simulator Icon

  2. In the Event Simulator panel, click Feed Simulation -> Create.

    Feed Simulation tab

  3. In the new panel that opens, enter information as follows:

    Random Simulation

    1. In the Simulation Name field, enter AggregateOverTime as the name for the simulation.

    2. Select Random as the simulation source and then click Add Simulation Source.

    3. In the Siddhi App Name field, select AggregateOverTime.

    4. In the Stream Name field, select Trade Stream.

    5. In the trader(STRING) field, select Regex based. Then in the Pattern field that appears, enter (Bob|Jane|Tom) as the pattern.

      Tip

      When you use the (Bob|Jane|Tom) pattern, only Bob, Jane, and Tom are selected as values for the trader attribute of the TradeStream. Using a few values for the trader attribute is helpful when you verify the output because the output is grouped by the trader.

    6. In the quantity(INT) field, select Primitive based.

    7. Save the simulator configuration by clicking Save.

    The newly created simulation is now listed under the Active Feed Simulations list as shown below.

    Newly Created Simulation

  4. Click the start button next to the AggregateOverTime simulation to start generating random events.

    Start

    In the Run or Debug dialog box that appears, select Run and click Start Similation.

    Start Simulation

Viewing the Results

Once you start the simulator, the output is logged in the console as shown in the sample below. The output reflects the aggregation for the events sent during the last 10 seconds.

Sample Random Events

Click here to view the sample Siddhi application.
@App:name("AggregateOverTime")

@App:description('Simulate multiple random events and calculate aggregations over time with group by')

define stream TradesStream(trader string, quantity int);
@sink(type='log')
define stream SummarizedTradingInformation(trader string, noOfTrades long, totalTradingQuantity long, minTradingQuantity int, maxTradingQuantity int, avgTradingQuantity double);

--Find count, sum, min, max and avg of quantity per trader, during the last 10 seconds
@info(name='query1')
from TradesStream#window.time(10 sec)
select trader, count() as noOfTrades, sum(quantity) as totalTradingQuantity, min(quantity) as minTradingQuantity, max(quantity) as maxTradingQuantity, avg(quantity) as avgTradingQuantity
group by trader
insert into SummarizedTradingInformation;
Top